Alignment statistics
GFP reads (genetic system validation)
PCC replicates
PCA replicates (QC, norm counts)
PCA conditions (compare conditions, log2FC)
MA plots (diff genes)
Alluvial plots (transitions between conditions)
Gene overlaps between conditions
Heatmap logFC genes of interest
GO up and down genes per condition
PCC between replicates (QC)
MA plots (diff regions)
Clustering figure Col1 -> Clustering heatmaps Col2 -> chromhmm SA2020 PH peaks type SA2020 FPKM W18 condition Col3 -> STRING network of interacting proteins, colored by cluster Col4 -> GO/cluster, depending on PRC1 binding (SA2020 assignment) Col5 -> Motif enrichment/cluster, depending on PRC1 binding (SA2020 assignment)
Plot cluster features depending on PRC1 binding (SA2020 assignment)
MA plots (diff regions)
4/ RECOVERY vs NO RECOVERY Defined as K27me+ & PRC1 bound (SA2020 assignment) &: PHD9 -> log2FoldChange_PHD9_vs_PH29<(-1) & padj_PHD9_vs_PH29<(0.05) –> RECOVERY else if log2FoldChange_PHD9_vs_WKD>0 ————————-> NORECOVERY PHD11 -> log2FoldChange_PHD11_vs_PH29<(-1) & padj_PHD11_vs_PH29<(0.05) -> RECOVERY else if log2FoldChange_PHD11_vs_WKD>0 ————————-> NORECOVERY Table
FPKM, overlaps between then and with clusters
Screenshots CUTNRUN & RNA blue: PH18, green: PHD11, magenta: PH29
Average tracks PH18/ctl conditions centered on PROMOTERS
Average tracks PH18/ctl conditions centered on most proximal ATAC peaks (REs)
Average tracks between conditions centered on promoters
Motif enrichment at proximal ATAC peaks (REs) and PROMOTERS
In my first attempt in using these clusters, we did not see much difference But I did not filter the genes for being PRC1 bound and K27me3+! Now it seems promising
Average tracks PH18/ctl conditions centered on PROMOTERS
Average tracks PH18/ctl conditions centered on most proximal PH peaks (REs)
Average tracks between conditions centered on promoters
Average tracks between conditions centered on promoters
Motif enrichment at PROMOTERS, proximal ATAC peaks (REs) and proximal PH peaks (ED ChIP-Seq)